The present invention relates to the field of optical correlators.
Real time pattern recognition is one of the most important applications of optical data processing. Since optical correlator architectures can recognize the appearance of an object in the presence of noise, many real time optical pattern recognition systems have been proposed in recent years For some applications, the light efficiency of the classical correlators is not sufficient. This problem can be avoided by using phase-only matched filters in optical correlator systems.
Recently, we introduced a binary nonlinear image correlator with substantially superior performance compared with that of the classical optical correlator. See B. Javidi and J. L. Horner, "Single Spatial Light Modulator Joint Transform Correlator," Appl. Opt. 28, 1027-1032 (1989). This optical processor is a joint Fourier transform correlator based system which allows both the input scene and the reference objects to be updated in real time. The binary nonlinear image correlator uses binarization at the Fourier plane to threshold the Fourier transform interference intensity. The performance of the nonlinear optical correlator has been compared with that of the classical optical correlator in the areas of light efficiency, correlation peak to sidelobe ratio, autocorrelation width, and cross-correlation sensitivity. It was shown that compared with the classical correlator, the binary nonlinear joint transform correlator provides significantly higher peak intensity, larger peak to sidelobe ratio, narrower autocorrelation width, and better cross-correlation sensitivity. Since the autocorrelation functions have small width, larger reference images can be used, and the restriction on the locations of the images and their autocorrelation width, which exists for the classical joint transform correlator, is eliminated.